scholarly journals Dynamic maintenance of planar digraphs, with applications

Algorithmica ◽  
1990 ◽  
Vol 5 (1-4) ◽  
pp. 509-527 ◽  
Author(s):  
Roberto Tamassia ◽  
Franco P. Preparata
Keyword(s):  
Author(s):  
Jimmy Ming-Tai Wu ◽  
Qian Teng ◽  
Shahab Tayeb ◽  
Jerry Chun-Wei Lin

AbstractThe high average-utility itemset mining (HAUIM) was established to provide a fair measure instead of genetic high-utility itemset mining (HUIM) for revealing the satisfied and interesting patterns. In practical applications, the database is dynamically changed when insertion/deletion operations are performed on databases. Several works were designed to handle the insertion process but fewer studies focused on processing the deletion process for knowledge maintenance. In this paper, we then develop a PRE-HAUI-DEL algorithm that utilizes the pre-large concept on HAUIM for handling transaction deletion in the dynamic databases. The pre-large concept is served as the buffer on HAUIM that reduces the number of database scans while the database is updated particularly in transaction deletion. Two upper-bound values are also established here to reduce the unpromising candidates early which can speed up the computational cost. From the experimental results, the designed PRE-HAUI-DEL algorithm is well performed compared to the Apriori-like model in terms of runtime, memory, and scalability in dynamic databases.


1988 ◽  
Vol 64 (5) ◽  
pp. 1968-1978 ◽  
Author(s):  
P. C. Kosch ◽  
A. A. Hutchinson ◽  
J. A. Wozniak ◽  
W. A. Carlo ◽  
A. R. Stark

To investigate airflow regulation in newborn infants, we recorded airflow, volume, diaphragm (Di), and laryngeal electromyogram (EMG) during spontaneous breathing in eight supine unsedated sleeping full-term neonates. Using an esophageal catheter electrode, we recorded phasic respiratory activity consistent with that of the principal laryngeal abductors, the posterior cricoarytenoids (PCA). Sequential activation of PCA and Di preceded inspiration. PCA activity typically peaked early in inspiration followed by either a decrescendo or tonic EMG activity of variable amplitude during expiration. Expiratory airflow retardation, or braking, accompanied by expiratory prolongation and reduced ventilation, was commonly observed. In some subjects we observed a time interval between PCA onset and a sudden increase in expiratory airflow just before inspiration, suggesting that release of the brake involved an abrupt loss of antagonistic adductor activity. Our findings suggest that airflow in newborn infants is controlled throughout the breathing cycle by the coordinated action of the Di and the reciprocal action of PCA and laryngeal adductor activities. We conclude that braking mechanisms in infants interact with vagal reflex mechanisms that modulate respiratory cycle timing to influence both the dynamic maintenance of end-expiratory lung volume and ventilation.


Author(s):  
Ahmed Al-Shammari ◽  
Chengfei Liu ◽  
Mehdi Naseriparsa ◽  
Bao Quoc Vo ◽  
Tarique Anwar ◽  
...  

Author(s):  
Yifan Dong ◽  
Tangbin Xia ◽  
Lei Xiao ◽  
Ershun Pan ◽  
Lifeng Xi

Abstract Real-time condition acquisition and accurate time-to-failure (TTF) prognostic of machines are both crucial in the condition based maintenance (CBM) scheme for a manufacturing system. Most of previous researches considered the degradation process as a population-specific reliability characteristics and ignored the hidden differences among the degradation process of individual machines. Moreover, existing maintenance scheme are mostly focus on the manufacturing system with fixed structure. These proposed maintenance scheme could not be applied for the reconfigurable manufacturing system, which is quite adjustable to the various product order and customer demands in the current market. In this paper, we develop a systematic predictive maintenance (PM) framework including real-time prognostic and dynamic maintenance window (DMW) scheme for reconfigurable manufacturing systems to fill these gaps. We propose a real-time Bayesian updating prognostic model using sensor-based condition information for computing each individual machine’s TTFs, and a dynamic maintenance window scheme for the maintenance work scheduling of a reconfigurable manufacturing system. This enables the real-time prognosis updating, the rapid decision making for reconfigurable manufacturing systems, and the notable maintenance cost reduction.


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